U.S. patent application number 14/884136 was filed with the patent office on 2016-10-20 for non-transitory computer readable medium, information processing apparatus, and information processing method.
This patent application is currently assigned to FUJI XEROX CO., LTD.. The applicant listed for this patent is FUJI XEROX CO., LTD.. Invention is credited to Masahiro SATO.
Application Number | 20160307220 14/884136 |
Document ID | / |
Family ID | 57129820 |
Filed Date | 2016-10-20 |
United States Patent
Application |
20160307220 |
Kind Code |
A1 |
SATO; Masahiro |
October 20, 2016 |
NON-TRANSITORY COMPUTER READABLE MEDIUM, INFORMATION PROCESSING
APPARATUS, AND INFORMATION PROCESSING METHOD
Abstract
A non-transitory computer readable medium stores a program
causing a computer to execute a process for estimating
willingness-to-buy. The process includes calculating including
diving a first operation history of multiple operations performed
by a user in electronic commerce, the dividing being performed on a
basis of one of the multiple operations, calculating a degree of
willingness-to-buy indicated by the one operation, the calculating
being performed on a basis of multiple operations included in a
second operation history obtained by dividing the first operation
history, and calculating a temporal change in a degree of
willingness-to-buy of the user in the electronic commerce.
Inventors: |
SATO; Masahiro; (Kanagawa,
JP) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
FUJI XEROX CO., LTD. |
Tokyo |
|
JP |
|
|
Assignee: |
FUJI XEROX CO., LTD.
Tokyo
JP
|
Family ID: |
57129820 |
Appl. No.: |
14/884136 |
Filed: |
October 15, 2015 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 30/0202
20130101 |
International
Class: |
G06Q 30/02 20060101
G06Q030/02 |
Foreign Application Data
Date |
Code |
Application Number |
Apr 17, 2015 |
JP |
2015-084793 |
Claims
1. A non-transitory computer readable medium storing a program
causing a computer to execute a process for estimating
willingness-to-buy, the process comprising: calculating including
diving a first operation history of a plurality of operations
performed by a user in electronic commerce, the dividing being
performed on a basis of one of the plurality of operations,
calculating a degree of willingness-to-buy indicated by the one
operation, the calculating being performed on a basis of a
plurality of operations included in a second operation history
obtained by dividing the first operation history, and calculating a
temporal change in a degree of willingness-to-buy of the user in
the electronic commerce.
2. The non-transitory computer readable medium according to claim
1, wherein a plurality of degrees of willingness-to-buy are
respectively calculated for the plurality of operations included in
the first operation history, and the temporal change in the degree
of willingness-to-buy of the user in the electronic commerce is
calculated on a basis of the calculated plurality of degrees of
willingness-to-buy, the process further comprising: acquiring a
change trend from the temporal change in the degree of
willingness-to-buy; and performing sales promotion on a basis of
the acquired change trend.
3. The non-transitory computer readable medium according to claim
1, the process further comprising: correcting the calculated
temporal change in the degree of willingness-to-buy by performing
smoothing.
4. The non-transitory computer readable medium according to claim
2, the process further comprising: correcting the calculated
temporal change in the degree of willingness-to-buy by performing
smoothing.
5. An information processing apparatus comprising: a calculation
unit that divides, on a basis of one of a plurality of operations
performed by a user in electronic commerce, a first operation
history of the plurality of operations, that calculates, on a basis
of a plurality of operations included in a second operation history
obtained by dividing the first operation history, a degree of
willingness-to-buy indicated by the one operation, and that
calculates a temporal change in a degree of willingness-to-buy of
the user in the electronic commerce.
6. An information processing method comprising: calculating
including diving a first operation history of a plurality of
operations performed by a user in electronic commerce, the dividing
being performed on a basis of one of the plurality of operations,
calculating a degree of willingness-to-buy indicated by the one
operation, the calculating being performed on a basis of a
plurality of operations included in a second operation history
obtained by dividing the first operation history, and calculating a
temporal change in a degree of willingness-to-buy of the user in
the electronic commerce.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is based on and claims priority under 35
USC 119 from Japanese Patent Application No. 2015-084793 filed Apr.
17, 2015.
BACKGROUND
Technical Field
[0002] The present invention relates to a non-transitory computer
readable medium, an information processing apparatus, and an
information processing method.
SUMMARY
[0003] According to an aspect of the invention, there is provided a
non-transitory computer readable medium storing a program causing a
computer to execute a process for estimating willingness-to-buy.
The process includes calculating including diving a first operation
history of multiple operations performed by a user in electronic
commerce, the dividing being performed on a basis of one of the
multiple operations, calculating a degree of willingness-to-buy
indicated by the one operation, the calculating being performed on
a basis of multiple operations included in a second operation
history obtained by dividing the first operation history, and
calculating a temporal change in a degree of willingness-to-buy of
the user in the electronic commerce.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] Exemplary embodiments of the present invention will be
described in detail based on the following figures, wherein:
[0005] FIG. 1 is a block diagram illustrating a configuration
example of an information processing apparatus according to an
exemplary embodiment;
[0006] FIG. 2 is a schematic diagram illustrating a display example
of a web page for browsing and purchasing an item;
[0007] FIG. 3 is a diagram for explaining an operation of
calculating degrees of willingness-to-buy;
[0008] FIG. 4 is a graph illustrating an example of an operation of
correcting a degree of willingness-to-buy (hereinafter, referred to
as a degree-of-willingness-to-buy correction operation);
[0009] FIG. 5 is a graph illustrating another example of the
degree-of-willingness-to-buy correction operation;
[0010] FIG. 6 is a graph illustrating yet another example of the
degree-of-willingness-to-buy correction operation; and
[0011] FIG. 7 is a flowchart illustrating an example of operation
of the information processing apparatus.
DETAILED DESCRIPTION
Exemplary Embodiment
Configuration of Information Processing Apparatus
[0012] FIG. 1 is a block diagram illustrating a configuration
example of an information processing apparatus according to an
exemplary embodiment.
[0013] An information processing apparatus 1 includes a controller
10, a memory 11, and a communication unit 12. The controller 10
includes a central processing unit (CPU) and other components,
controls units of the information processing apparatus 1, and
executes various programs. The memory 11 includes a storage medium
such as a flash memory and is used to store information. The
communication unit 12 communicates with external apparatuses
through a network.
[0014] The controller 10 executes a willingness-to-buy estimation
program 110 (described later) to thereby function as an
operation-history acquisition unit 100, a user-identification
determination unit 101, an operation-history division unit 102, a
degree-of-willingness-to-buy calculation unit 103, a
degree-of-willingness-to-buy correction unit 104, a change-trend
acquisition unit 105, a sales promotion unit 106, and other
units.
[0015] The operation-history acquisition unit 100 acquires, from a
service provider that provides services of electronic commerce,
operation-history information 111 indicating a history of
operations having been performed when a user has browsed and
purchased items, for example, by electronic commerce in the past.
In the electronic commerce, items and services are sold, purchased,
and distributed through electronic information communications
performed on a computer network. As the operation history, a
history of clicks on a link and the like on a web page for
providing an electronic commerce service may be recorded. Further,
information such as the duration of browsing the web page, the
number of browsed pages, and the order of page transitions may be
recorded.
[0016] The user-identification determination unit 101 identifies a
user who has performed multiple operations included in the
operation-history information 111 and handles, as a history of
operations, a series of operations performed by the same user.
Further, the user-identification determination unit 101 handles, as
a session, a series of operations performed in temporal succession
in the history of the series of operations. Note that in the
session, a series of communications are performed when the user
utilizes an electronic commerce service. To define sessions,
sessions are divided on the basis of, for example, an interval in
which no communication is performed within a predetermined
time.
[0017] The operation-history division unit 102 divides an operation
history of multiple operations included in a specific session by
using each operation as a reference operation. The
operation-history division unit 102 thus obtains multiple operation
histories respectively corresponding to multiple periods each
including operations from the first operation to the corresponding
reference operation. For example, in a case where operations in a
specific session are from Click 1 to Click 8, an operation history
of the operations is divided to obtain multiple operation histories
in the following manner. Specifically, based on Click 1, an
operation history of the operation (Click 1) included in a period
from the operation start to a time point of Click 1 is obtained.
Based on Click 2, an operation history of the operations (Clicks 1
and 2) included in a period from the operation start to a time
point of Click 2 is obtained. Based on Click 3, an operation
history of the operations (Clicks 1, 2, and 3) included in a period
from the operation start to a time point of Click 3 is
obtained.
[0018] The degree-of-willingness-to-buy calculation unit 103
calculates the degree of willingness-to-buy of the user observed at
the time point of each operation, on the basis of the corresponding
operation history of the period obtained by the division performed
by the operation-history division unit 102. The
degree-of-willingness-to-buy calculation unit 103 stores, in the
memory 11, the result as degree-of-willingness-to-buy information
112. Note that the degree of willingness-to-buy may be calculated
by using any technique, for example, by performing clustering on
the basis of a common subsequence in a clickstream (Clickstream
Clustering using Weighted Longest Common Subsequences, Arindam
Banerjee and Joydeep Ghosh, SIAM, 2001) or a technique of
predicting whether a user will purchase an item and the number of
purchases of the item on the basis of time spent on a web page and
the number of browsed pages (From Amazon to Apple-Modeling Online
Retail Sales and Visit Behavior, Anastasios Panagiotelis, Michael
S. Smith and Peter Danaher Journal of Business and Economic
Statistics, 2013).
[0019] The degree-of-willingness-to-buy correction unit 104
corrects, in accordance with a predetermined criterion, the
degree-of-willingness-to-buy information 112 calculated by the
degree-of-willingness-to-buy calculation unit 103 and stores the
result in the memory 11 as corrected degree-of-willingness-to-buy
information 113. The correction is performed by using, for example,
machine learning or pattern recognition. Specific examples of the
correction will be described in detail in "Operation of Information
Processing Apparatus".
[0020] On the basis of temporal changes in degree of
willingness-to-buy, the change-trend acquisition unit 105 acquires
a change trend indicating, for example, a user is less or more
willing to buy an item.
[0021] The sales promotion unit 106 performs sales promotion on the
basis of the change trend acquired by the change-trend acquisition
unit 105. For example, the sales promotion unit 106 performs sales
promotion such as by presenting a discount coupon to the user in
the case where the user is less willing to buy the item or by
removing an advertisement in the case where the user is more
willing to buy the item.
[0022] The memory 11 is used to store the willingness-to-buy
estimation program 110 causing the controller 10 to function as the
units 100 to 106 described above, the operation-history information
111, the degree-of-willingness-to-buy information 112, the
corrected degree-of-willingness-to-buy information 113, and the
like.
Operation of Information Processing Apparatus
[0023] Next, (1) Basic Operation, (2) Degree-of-willingness-to-buy
Calculation Operations, and (3) Sales Promotion Operation will be
described as actions of the present exemplary embodiment.
(1) Basic Operation
[0024] FIG. 2 is a schematic diagram illustrating a display example
of a web page for browsing and purchasing an item.
[0025] First, a user accesses a web page to browse a desired item
by using a terminal apparatus, for example, a personal computer
(PC) of the user, the web page being managed by a server of an
electronic commerce service provider. The terminal apparatus
processes information transmitted from the server, and a web-page
display screen 20 is thereby displayed on the display of the
terminal apparatus, as illustrated in FIG. 2.
[0026] The web-page display screen 20 includes a menu display 200,
an item information display 201, and a sales-promotion information
display 202. The menu display 200 includes an input box for
searching for an item, a selection button for selecting an item
category, and the like. The item information display 201 includes
photos, the name, and the price of an item, various buttons for
purchasing the item, and the like. The sales-promotion information
display 202 displays information for sales promotion in such a
manner as to change the content of the information in accordance
with the degree of willingness-to-buy of the user who is browsing
an item displayed in the item information display 201.
[0027] The sales-promotion information display 202 displays a
discount coupon 202a for a discount on the price of the item, an
advertisement 202b related to the item or matching the taste of the
user, and the like.
[0028] The server of the service provider records, as
operation-history information, information caused by the user to be
displayed on the web-page display screen 20 and operations
performed on the web-page display screen 20.
[0029] The server of the service provider also transmits the
operation-history information to the information processing
apparatus 1 to request the information processing apparatus 1 to
transmit information regarding an item to be displayed in the
sales-promotion information display 202.
(2) Degree-of-Willingness-to-Buy Calculation Operations
[0030] FIG. 7 is a flowchart illustrating an example of operation
of the information processing apparatus 1.
[0031] The operation-history acquisition unit 100 acquires the
operation-history information from the service provider and stores
the operation-history information as the operation-history
information 111 in the memory 11 (S1).
[0032] The user-identification determination unit 101 identifies a
user who has performed multiple operations included in the
operation-history information 111 and handles, as a history of
operations, a series of operations performed by the same user.
Further, the user-identification determination unit 101 handles, as
a session, a series of operations performed in temporal succession
in the history of the series of operations and thus divides the
history of the series of operations on a per-session basis
(S2).
[0033] FIG. 3 is a diagram for explaining an operation of
calculating degrees of willingness-to-buy.
[0034] The operation-history division unit 102 divides a history of
sequential operations included in a specific session by using each
operation as a reference operation and thus obtains multiple
operation histories. For example, as illustrated in FIG. 3, in a
case where operations in a specific session are from Click 1 to
Click 8, an operation history of the operations is divided to
obtain multiple operation histories in the following manner.
Specifically, based on Click 1, an operation history of the
operation (Click 1) included in a period from the operation start
to a time point of Click 1 is obtained. Based on Click 2, an
operation history of a series of operations (Clicks 1 and 2)
included in a period from the operation start to a time point of
Click 2 is obtained. Based on Click 3, an operation history of a
series of operations (Clicks 1, 2, and 3) included in a period from
the operation start to a time point of Click 3 is obtained
(S4).
[0035] The degree-of-willingness-to-buy calculation unit 103
calculates degrees of willingness-to-buy 112a.sub.1 to 112a.sub.8
of the user at the time points of the respective operations, the
calculation being performed on the basis of the operation histories
corresponding to the periods resulting from the division performed
by the operation-history division unit 102 (S5). The
degree-of-willingness-to-buy calculation unit 103 stores the
calculation results as the degree-of-willingness-to-buy information
112 in the memory 11. Steps S4 and S5 described above are performed
for each period (S3, S6, and S7). Specifically, the calculation is
performed in such a manner that the degree of willingness-to-buy
112a.sub.1 is calculated on the basis of Click 1, the degree of
willingness-to-buy 112a.sub.2 is calculated on the basis of Clicks
1 and 2, and the degree of willingness-to-buy 112a.sub.3 is
calculated on the basis of Clicks 1, 2, and 3. Note that when the
degrees of willingness-to-buy are calculated, all of the clicks
from the start of operations do not have to be used, and a
predetermined number of operations may be used. For example, in a
case where the predetermined number of operations is 3, the degree
of willingness-to-buy 112a.sub.5 may be calculated on the basis of
Clicks 3, 4, and 5. In addition, sequential operations do not have
to be used, and the degree of willingness-to-buy 112a.sub.5 may be
calculated on the basis of Clicks 1, 3, and 5.
[0036] As in Degree-of-willingness-to-buy Correction Operations 1
to 3 (described later), the degree-of-willingness-to-buy correction
unit 104 corrects, in accordance with a predetermined criterion,
the degree-of-willingness-to-buy information 112 calculated by the
degree-of-willingness-to-buy calculation unit 103 (S8). The
degree-of-willingness-to-buy correction unit 104 stores the result
as the corrected degree-of-willingness-to-buy information 113 in
the memory 11.
(2-1) Degree-of-Willingness-to-Buy Correction Operation 1
[0037] FIG. 4 is a graph illustrating an example of a
degree-of-willingness-to-buy correction operation.
[0038] The degree-of-willingness-to-buy correction unit 104
performs smoothing by using a method such as a spline or a moving
average on the assumption that the degree of willingness-to-buy
continuously changes over time and obtains a corrected
degree-of-willingness-to-buy 113a indicated by the dotted line in
FIG. 4.
(2-2) Degree-of-Willingness-to-Buy Correction Operation 2
[0039] FIG. 5 is a graph illustrating another example of the
degree-of-willingness-to-buy correction operation.
[0040] The degree-of-willingness-to-buy correction unit 104
performs smoothing on the basis of values of the degrees of
willingness-to-buy other than abnormal values 104a and 104b
illustrated in FIG. 5 that largely deviate from a trend of the
degree of willingness-to-buy and obtains a corrected
degree-of-willingness-to-buy 113b indicated by the dotted line.
(2-3) Degree-of-Willingness-to-Buy Correction Operation 3
[0041] FIG. 6 is a graph illustrating yet another example of the
degree-of-willingness-to-buy correction operation.
[0042] The degree-of-willingness-to-buy correction unit 104 causes
the degree-of-willingness-to-buy calculation unit 103 to calculate
degrees of willingness-to-buy by using multiple techniques,
methods, or prediction models, respectively, and performs
comparison between degrees of willingness-to-buy 112b and 112c thus
obtained as illustrated in FIG. 6. The degree of willingness-to-buy
112b is a calculation result exhibiting a smaller change in the
degree of willingness-to-buy, and thus the
degree-of-willingness-to-buy correction unit 104 uses the degree of
willingness-to-buy 112b as a corrected degree of
willingness-to-buy.
(3) Sales Promotion Operation
[0043] The change-trend acquisition unit 105 acquires a change
trend from a temporal change in the degree of willingness-to-buy,
the change trend indicating, for example, whether the user is less
or more willing to by the item (S9). For example, in the example in
FIG. 3, the change-trend acquisition unit 105 acquires a change
trend indicating that the user is less likely to buy the item in a
period of the degrees of willingness-to-buy 112a.sub.2 to
112a.sub.5 corresponding to Click 2 to Click 5 and that the user is
more likely to buy the item in a period of the degrees of
willingness-to-buy 112a.sub.5 to 112a.sub.8 corresponding to Click
5 to Click 8.
[0044] The sales promotion unit 106 performs sales promotion on the
basis of the change trend acquired by the change-trend acquisition
unit 105 (S10). For example, in a case where the user is less
likely to buy the item as in the period from Click 2 to Click 5 in
FIG. 3, the sales promotion unit 106 presents the discount coupon
202a related to the browsed item in the sales-promotion information
display 202 in FIG. 2 to encourage the user to buy the item. In a
case where the user is more likely to buy the item as in the period
from Click 5 to Click 8, the sales promotion unit 106 performs
sales promotion such as by removing the advertisement 202b
displayed in the sales-promotion information display 202 to make
the user concentrate on the browsed item.
Other Exemplary Embodiments
[0045] Note that the present invention is not limited to the
exemplary embodiment described above, and various modifications may
be made without departing from the gist of the present
invention.
[0046] The functions of the units 100 to 106 of the controller 10
are implemented by using the program in the exemplary embodiment,
but all or some of the units may be implemented by hardware such as
an application specific integrated circuit (ASIC). In addition, the
program used in the exemplary embodiment described above may be
provided in such a manner as to be stored in a recording medium
such as a compact disc read-only memory (CD-ROM). Moreover, mutual
changes, deletions, additions, and the like of steps described
above in the aforementioned exemplary embodiment may be made
without departing from the gist of the present invention.
[0047] The foregoing description of the exemplary embodiments of
the present invention has been provided for the purposes of
illustration and description. It is not intended to be exhaustive
or to limit the invention to the precise forms disclosed.
Obviously, many modifications and variations will be apparent to
practitioners skilled in the art. The embodiments were chosen and
described in order to best explain the principles of the invention
and its practical applications, thereby enabling others skilled in
the art to understand the invention for various embodiments and
with the various modifications as are suited to the particular use
contemplated. It is intended that the scope of the invention be
defined by the following claims and their equivalents.
* * * * *